Permutation Tests for Regression, (Repeated Measures) ANOVA/ANCOVA and Comparison of Signals
P-values based on permutation tests for ANOVA and repeated measures AN...
Method to convert into Pmat object.
Cluster-mass test for longitudinal data
Cluster-depth correction (from the head only)
Cluster-depth correction
Clustermass test correction
The max-T correction
The min-P correction
Step-down version of the max-T correction
Threshold-Free Cluster-Enhancement correction
The Troendle's correction
Get the ID of the cluster on a distribution matrix
Permutation tests for regression parameters
Plot cluster or parameters.
Plot method for class "lmperm".
Multiplies a vector with a Pmat object
Create a set of permutations/signflips.
Print clusterlm object.
Summarize of a clusterlm object.
Functions to compute p-values based on permutation tests. Regression, ANOVA and ANCOVA, omnibus F-tests, marginal unilateral and bilateral t-tests are available. Several methods to handle nuisance variables are implemented (Kherad-Pajouh, S., & Renaud, O. (2010) <doi:10.1016/j.csda.2010.02.015> ; Kherad-Pajouh, S., & Renaud, O. (2014) <doi:10.1007/s00362-014-0617-3> ; Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014) <doi:10.1016/j.neuroimage.2014.01.060>). An extension for the comparison of signals issued from experimental conditions (e.g. EEG/ERP signals) is provided. Several corrections for multiple testing are possible, including the cluster-mass statistic (Maris, E., & Oostenveld, R. (2007) <doi:10.1016/j.jneumeth.2007.03.024>) and the threshold-free cluster enhancement (Smith, S. M., & Nichols, T. E. (2009) <doi:10.1016/j.neuroimage.2008.03.061>).
Useful links